Capstone Project - Pnemonia detection

Milestone 1

Step 1: Import the data.

Step 2: Map training and testing images to its classes.

Step 3: Map training and testing images to its annotations.

Step 4: Preprocessing and Visualisation of different classes

Step 5: Display images with bounding box.

Step 6: Design, train and test basic CNN models for classification.

Milestone 2

Step 1: Fine tune the trained basic CNN models for classification.

CNN tuned

Step 2: Apply Transfer Learning model for classification

Resnet50

VGGNet16

InceptionV2

Classification Model Results

Step 3: Design, train and test RCNN & its hybrids based object detection models to impose the bounding box or mask over the area of interest.

Faster RCNN - Using gluoncv

UNET - Use binary segmentation for detection

Step 4: Pickle the model for future prediction

Optional: Design a clickable UI based interface which can browse & input the image, output the class & bounding box or mask (highlight area of interest) of the input image